B2B Service Business - AI Chat Traffic & GEO Growth

A B2B service business wanted to improve visibility beyond traditional Google search. Their existing SEO was bringing in organic traffic, but they were not yet earning meaningful visibility from AI chat platforms where buyers were increasingly researching services, comparing providers and asking for recommendations. The client operated in a competitive B2B service market where trust, expertise and clarity were essential. They already had some organic visibility, but their website was not structured in a way that made it easy for AI systems to understand, retrieve and reference their expertise. The main issues were: • Service pages were useful but not deep enough • The website lacked clear topical clusters around core services • FAQs were limited or missing from key commercial pages • First-hand expertise was not being used properly in content • AI crawlers had no clear site-level guidance through llms.txt • The site had few strong pages built around original insights, data or practical experience The business did not just need more generic SEO content. It needed stronger evidence of expertise. For AI search, that distinction matters.

We implemented a full GEO strategy using comprehensive llms.txt and full-llms.txt files, improved service content, built stronger topical authority and created insight-led pages using the client’s own first-hand data. LLMs.txt and Full-LLMs.txt Implementation We created and deployed a comprehensive llms.txt file to help AI systems understand the business, its services, its core expertise and the most important pages on the website. We also created a more detailed full-llms.txt file with deeper page-level context, service summaries and structured explanations of the company’s knowledge areas. This helped give AI crawlers a clearer map of the site and reduced the risk of key content being misunderstood or ignored. The files were structured to highlight core services, important service pages, resource pages, insight pages, FAQs, business context, areas of expertise and content that should be prioritised for understanding. Topical Authority Around Core Services We then built stronger topical authority around the client’s main services. Instead of treating each service page as a standalone page, we built supporting content around the questions, comparisons, problems and decision points that buyers actually care about. This included: • Core service page improvements • Supporting educational pages • Comparison-style content • Problem-led content • Buyer questions • Internal linking between related pages • Clearer content hierarchy • Stronger page summaries and definitions This made the site easier for both Google and AI systems to understand as a credible source within its service category. Content Optimisation and FAQs We improved the structure of key pages so they were easier to read, extract and reference. This included clearer headings, better summaries, stronger internal links and FAQ sections on important pages. The FAQs were written to match the way real buyers ask questions, not just traditional keyword variations. This helped the site answer more conversational queries, which is especially important for AI search and chat-led discovery. First-Hand Data and Insight-Led Pages The biggest driver was not the technical setup alone. It was the use of first-hand data. We worked with the client’s own experience, internal knowledge and business data to create insight-led pages that could not easily be replicated by generic AI-written content. These pages added original value by showing real patterns from the client’s market, practical lessons from service delivery, common client problems, decision-making insights, first-hand observations, data-backed recommendations and clear explanations from real experience. This gave AI systems stronger source material to reference because the content was not just repeating what already existed online. It added information gain.

The GEO work produced a clear increase in visibility from AI chat platforms. AI chat traffic is now close to matching the client’s organic search traffic, showing that AI-led discovery has become a meaningful acquisition channel for the business. Key outcomes included: • AI chat traffic grew to almost the same level as organic search traffic • Stronger visibility across AI-led discovery journeys • Improved service page clarity and depth • Better topical authority around core services • Comprehensive llms.txt and full-llms.txt infrastructure deployed • More conversational queries matched through FAQ optimisation • First-hand data turned into high-value insight pages • Better internal linking between services and supporting content • Stronger evidence of expertise across the website This project showed that GEO is not just about adding an llms.txt file or rewriting pages for AI. Those elements helped, but the biggest performance driver was the creation of useful, original, insight-led content based on first-hand data. The business became easier for AI systems to understand because its content was clearer, deeper and better structured. More importantly, it had something worth referencing. The result was a new visibility channel that now performs close to organic search. For this B2B service business, AI chat traffic is no longer a small side effect. It has become a meaningful source of discovery, education and demand.